@article{ref1,
title="Examining drivers' eye glance patterns during distracted driving: insights from scanning randomness and glance transition matrix",
journal="Journal of safety research",
year="2017",
author="Wang, Yuan and Bao, Shan and Du, Wenjun and Ye, Zhirui and Sayer, James R.",
volume="63",
number="",
pages="149-155",
abstract="INTRODUCTION: Visual attention to the driving environment is of great importance for road safety. Eye glance behavior has been used as an indicator of distracted driving. This study examined and quantified drivers' glance patterns and features during distracted driving. <br><br>METHOD: Data from an existing naturalistic driving study were used. Entropy rate was calculated and used to assess the randomness associated with drivers' scanning patterns. A glance-transition proportion matrix was defined to quantity visual search patterns transitioning among four main eye glance locations while driving (i.e., forward on-road, phone, mirrors and others). All measurements were calculated within a 5s time window under both cell phone and non-cell phone use conditions. <br><br>RESULTS: Results of the glance data analyses showed different patterns between distracted and non-distracted driving, featured by a higher entropy rate value and highly biased attention transferring between forward and phone locations during distracted driving. Drivers in general had higher number of glance transitions, and their on-road glance duration was significantly shorter during distracted driving when compared to non-distracted driving. <br><br>CONCLUSIONS: Results suggest that drivers have a higher scanning randomness/disorder level and shift their main attention from surrounding areas towards phone area when engaging in visual-manual tasks. PRACTICAL APPLICATIONS: Drivers' visual search patterns during visual-manual distraction with a high scanning randomness and a high proportion of eye glance transitions towards the location of the phone provide insight into driver distraction detection. This will help to inform the design of in-vehicle human-machine interface/systems.<br><br>Copyright © 2017. Published by Elsevier Ltd.<p /> <p>Language: en</p>",
language="en",
issn="0022-4375",
doi="10.1016/j.jsr.2017.10.006",
url="http://dx.doi.org/10.1016/j.jsr.2017.10.006"
}